Antecedents and consequences of face filter use on social media: the role of use frequency and depth

Purpose Face filters are pervasive in selfie-based social media practices, raising concerns about their psychological implications. This study examines the social drivers of face-filter use frequency and depth, their positive and negative psychological consequences and how these two dimensions jointly shape user outcomes. Design/methodology/approach Drawing on self-discrepancy theory (SDT), we conceptualize descriptive and subjective norms as self-guides influencing two dimensions of filter use: frequency (which regulates discrepancy accessibility) and depth (which regulates discrepancy availability). We propose a model linking filter use to affective outcomes and self-evaluations and examine the interactive effects of use frequency and depth on these outcomes. The model was tested using survey data from 328 participants. Findings Descriptive and subjective norms positively predict use frequency and depth. Use frequency, but not use depth, increases self-confidence by enhancing appearance self-esteem; whereas both frequency and depth increase negative moods by amplifying self-discrepancy perceptions. Additionally, the interaction between use frequency and depth is positively associated with both appearance self-esteem and perceived self-discrepancy. Originality/value This study is among the first to integrate SDT and social norms to explain the antecedents and dual consequences of face-filter use. By distinguishing use frequency and depth as two self-regulation dimensions in digital self-presentation, this study highlights their main and interactive effects on positive and negative psychological outcomes and clarifies the underlying mechanisms.

Authors

Institutions

Publication Details

Journal
Information Technology and People
Published
2026-09-16
DOI
https://doi.org/10.1108/itp-09-2025-1335
Primary Topic
Evolutionary Psychology and Human Behavior
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
article

Antecedents and consequences of face filter use on social media: the role of use frequency and depth

Jingjun Xu, Jingjing Tong, Chunyi Xian
Information Technology and People
Evolutionary Psychology and Human Behavior
article

Antecedents and consequences of face filter use on social media: the role of use frequency and depth

Jingjun Xu, Jingjing Tong, Chunyi Xian
article en

Abstract

Purpose Face filters are pervasive in selfie-based social media practices, raising concerns about their psychological implications. This study examines the social drivers of face-filter use frequency and depth, their positive and negative psychological consequences and how these two dimensions jointly shape user outcomes. Design/methodology/approach Drawing on self-discrepancy theory (SDT), we conceptualize descriptive and subjective norms as self-guides influencing two dimensions of filter use: frequency (which regulates discrepancy accessibility) and depth (which regulates discrepancy availability). We propose a model linking filter use to affective outcomes and self-evaluations and examine the interactive effects of use frequency and depth on these outcomes. The model was tested using survey data from 328 participants. Findings Descriptive and subjective norms positively predict use frequency and depth. Use frequency, but not use depth, increases self-confidence by enhancing appearance self-esteem; whereas both frequency and depth increase negative moods by amplifying self-discrepancy perceptions. Additionally, the interaction between use frequency and depth is positively associated with both appearance self-esteem and perceived self-discrepancy. Originality/value This study is among the first to integrate SDT and social norms to explain the antecedents and dual consequences of face-filter use. By distinguishing use frequency and depth as two self-regulation dimensions in digital self-presentation, this study highlights their main and interactive effects on positive and negative psychological outcomes and clarifies the underlying mechanisms.

Information Technology and People
University of Science and Technology of China (CN), City University of Hong Kong (HK)
Reduced inequalities
Openalex Percentile: Top 7%
Evolutionary Psychology and Human Behavior
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.